Job Type: Full Time

Location:

Role Purpose

Appen’s GenAI Project Delivery team sits at the intersection of AI development and real-world data quality, executing the annotation, evaluation, and data collection work that shapes how frontier models perform. The purpose of this role is to drive end-to-end delivery excellence across GenAI projects by ensuring task configuration, contributor performance, and data quality outcomes stay tightly aligned to client expectations. This is a hands-on, cross-functional role with influence over delivery standards, client outcomes, and the continuous improvement of how Appen executes at scale.

Your Impact

What You Bring

• Strong understanding of data quality principles, QA methodologies, and annotation workflows within GenAI or adjacent AI domains.
• Ability to create clear, accurate contributor-facing documentation including guidelines and FAQs.
• Confident communicator with experience engaging cross-functional stakeholders, including client-facing participation in meetings, workshops, or reporting cycles.
• Comfortable operating across multiple concurrent workstreams with a high degree of ownership and attention to delivery standards.

Why You’ll Love Working Here

At Appen, we foster a culture of innovation, collaboration, and excellence. We value curiosity, accountability, and a commitment to delivering the highest quality AI solutions for frontier models. You’ll work on complex challenges that shape the future of AI across industries and geographies, alongside talented people in a culture that values humility over ego. You’ll have the flexibility to deliver in a way that works for you and your team, supported by tools, resources, and development opportunities to continue to build your capability over time.

About Appen

Appen has been a leader in AI training data for over 30 years. We specialise in human generated data to train, fine tune, and evaluate models across generative AI, large language models, computer vision, and speech recognition. Our AI assisted data annotation platform and global crowd of more than 1 million contributors in over 200 countries support model pre training, supervised fine tuning, evaluation and benchmarking, safety and red teaming, and multilingual global expansion.

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